6974 research outputs found
Sort by
Fighting the next pandemic?:Civil-military collaboration in health emergencies after COVID
No full textOver the past decade, militaries have been highly visible elements in the response to health emergencies and in particular disease outbreaks. Although there has been a long tradition of civil-military collaboration in health, COVID-19 saw an unprecedented worldwide use of militaries which occurred within a permissive environment established by narratives of global health, humanitarian intervention and multi-sectorality. This creates a dilemma that militaries will likely be an important element in responding to a major health emergency, but that this risks not only militarizing health emergencies but the balance between society and the military more generally. Moreover, the response to the COVID pandemic suggested that current emergency planning is often poorly prepared for the use of militaries in health crises, thereby reducing the effectiveness of a response. This article engages with how concerns over the securitization of health have evolved into concerns over militarization, and the question of how militaries might be used effectively in future health emergencies without risking the militarization of health or damaging civil-military relations more widely
Language-Guided Change Detection for high-resolution remote sensing imagery with limited labelled data
No full textDeep learning has been extensively applied in the field of remote sensing for tasks such as change detection (CD). However, since CD is a pixel-level task, the high cost of data annotation and often limited availability of labelled data significantly restrict the performance of existing deep learning-based CD methods. To mitigate this problem, a novel Language-Guided Change Detection (LGCD) framework is introduced. Within this LGCD network, text information is leveraged to precisely locate changed areas, addressing the shortcomings associated with insufficient labelled image data. Also, augmentation semi-supervised learning techniques are employed to generate high-quality pseudo-labels, further reducing the reliance on labelled samples. Additionally, the utilisation of Fusion UNet (FUNet) and Transformer capitalises on their sensitivity to local and global features respectively, offering a comprehensive examination of change features in high-resolution bi-temporal remote sensing imagery. For evaluation purposes, three publicly available CD datasets are exploited. Experimental results demonstrate that the proposed LGCD framework achieves exceptional detection performance in both fully supervised and semi-supervised settings, despite the constraints of limited labelled data.</p
Effects of sensory and environmental labelling of plant-based products on consumer acceptance:Context, energy density and framing factors
Full text linkThere is growing pressure to replace animal-sourced proteins with plant-based proteins. Consumer studies suggest sensory properties and environment are the major factors impacting adoption of PBFs, but few studies have contrasted these factors. Knowing that health labels negatively impact sensory experience, we tested whether environmental labels had the same negative impact. Using an online survey, volunteers (N = 328) were randomly assigned to one of three label contexts: sensory (emphasizing taste and texture), environmental (highlighting sustainability and environmental impact), or control (no specific messaging), where they evaluated eight plant-based alternative foods. Each product was enhanced by either a positive or a negatively valanced framing statement, with half the foods higher, and half lower, in energy density (ED). Participants rated expected liking, wanting and likely recommendation, and estimated what they would pay for each food. For liking and recommending, there was no significant difference between environmental and sensory contexts (p = 0.94), but both were significantly higher than control (p = 0.0006), while for expected wanting only the sensory exceeded the control (p = 0.0014). The amount willing to pay was significantly higher in the environmental than sensory (p = 0.0005) or control (p < 0.0001) contexts, which did not differ significantly (p = 0.49). For all four measures, higher ED foods were rated significantly more positively than lower ED (p < 0.001), while the effect of environment on purchase price was magnified by higher ED foods (p < 0.001). Positive framing statements were rated significantly higher than negative framing for liking (p < 0.001), wanting (p < 0.001) and recommending (p = 0.022), but not for purchase (p = 0.30). When habitual diet (plant-based or not) was included in the exploratory analyses, it only altered acceptance of lower energy-dense products in the control context. Overall, these data suggest that the use of environmental descriptors may enhance consumer expectations and willingness to pay more to the same degree as sensory descriptors, providing various strategies for marketers and product developers to promote PBFs based on messages that best fit the brand identity and expand the PBFs narrative beyond health
LPIA palaeo-fjords:new insights from northern Namibia
No full textA detailed understanding of the features produced beneath ice sheets, in terms of both their spatial distribution and their genesis, is crucial for a correct reading of the glacial record. An assemblage of features cut into crystalline bedrock in northern Namibia were produced approximately 300 myr ago during the Late Paleozoic Ice Age and exhibit an outstanding array of structures contained within deep palaeo-fjords, capped by glaciogenic rocks of the basal Dwyka Group. With the exception of a handful of recent studies in the last 3 years, this area has been largely ignored since the mid-twentieth century. By utilizing large-scale aerial and close-range photogrammetry, we map the subglacial substrate in the Eastern Hoarusib palaeovalley at an unprecedented resolution, marking the first time that large swarms of striae and other subglacial bedforms, such as crescentic markings, have been mapped. Quantitative analyses of macroscale ice flow features include around 17 000 measurements, reducing uncertainty regarding ice flow direction. In the Gomatum palaeovalley, c. 100 km to the SW, we utilize detailed micromorphology and sedimentological analyses to examine basal Dwyka Group strata, recognizing delicate dropstone-bearing laminae and micro-imbrication in heterolithic deposits (fining-upward sandstones and siltstones, rhythmic couplets) lying approximately 50–60 m above the present valley floor. These deposits are interpreted as ice-rafted debris and unidirectional current deposits, which testify to the presence of lingering ice during the transgression of the palaeovalleys. More widely, we argue that the quantitative photogrammetric approaches showcased herein could be more widely adopted in studies of the deep time glacial record and possibly benefit the research of Quaternary fjord systems
Identifying a cell wall ideotype for increased soil carbon contents associated with Miscanthus cultivation.
No full textDedicated biomass crops are widely accepted as an important part of decarbonising economies. Miscanthus is a leading dedicated biomass crop that embodies high yield with many co-benefits including soil carbon sequestration plus the benefits of perennial agronomy. Breeding programmes for Miscanthus are in their infancy but it is apposite to consider the potential for breeding improved soil carbon sequestration. We focussed on gross biomass inputs from leaf, roots and rhizome and examined both dry weight and cell wall composition as key factors that influence soil carbon sequestration. We measured lignin, cellulose, hemicellulose, carbon and nitrogen from all three tissues in different Miscanthus genotypes that had been grown in field plots and compared for soil carbon. There was a significant genotypic effect on most compositional traits from all three tissue types and composition also varied between tissue types. When combined with soil C data from field grown plants, lignin and lignin:N were shown to be useful predictive factors (along with soil depth) for total soil organic C and this combination of factors explained 86% of the model variance for Miscanthus derived soil C. Examples of trade-offs were observed but a high sequestering plant includes low root lignin and high belowground biomas
